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-cell transcriptomics and modern statistical/AI methodology to address this gap using in-house developed cell atlases. We will develop and benchmark approaches that infer copy-number changes and CIN
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– Molecular-Scale Modelling This PhD position focuses on molecular-scale computational modelling of polymer-hybrid anion-exchange membranes. The project involves DFT, molecular dynamics, and Monte Carlo
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, open, inclusive and collaborative, are great strengths. We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed. Please also
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experience with DFT codes will be very highly valued. • Knowledge of chemical reactions and how to model them through computer simulations is highly valued. • Knowledge of classical molecular dynamics
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CIIMAR - Interdisciplinary Center of Marine and Environmental Research - Uporto | Portugal | 22 days ago
-on experience in cyanobacterial cultivation, bioassays, genome sequencing and genome mining, preparation of extracts for metabolomics and protein assays, and molecular biology. Any national, foreign and stateless
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-0831 Description of Work: At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents
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/Qualifications Laboratory skills: 3D printing, polymers, composites, nanomaterials synthesis; Experience in molecular spectroscopy: practical skills in Raman, SERS, IR, and UV-Vis spectroscopy; analysis of various
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molecular biology approaches. The data generated will be relevant to our understanding of human diseases where NF-κB has been demonstrated to be important, such as inflammatory disease and cancer, and will be
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Student or Postdoc (f/m/d) in the field of Theory and Methods for Non-equilibrium Theory and Atomistic Simulations of Complex Biomolecules Possible projects are variational free energy methods
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the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc in Machine Learned Semiconductor Material Properties for Quantum Transport Simulations The simulation